Color information encoding in monochrome printing

ABSTRACT

An image processing system including a processor configured to analyze a color image to determine a set of target colors and a database including factor profiles associated with a set of stored colors. The image processing system further includes a printer controller that assigns the factor profiles to the target colors according to a color space proximity of the target colors with the stored colors. The factor profiles represent a combination of factors including a gray level and a screen angle.

TECHNICAL FIELD

The invention relates to the retention of color information in arendered monochrome print.

BACKGROUND

Printing a color image as a monochrome print involves converting theinput colors into various levels or shades of a monochrome color, suchas gray. The number of colors that may be generated and displayed on aconventional monitor are typically many more times that of the number oflevels of gray which a printer is able to print. In addition to theprinter being unable to represent each color as a unique gray level, thecolor information itself is typically lost during the color conversionand subsequent printing of the monochrome image.

Conventional systems have attempted to retain color information in amonochrome print by analyzing individual pixels arranged within ahalftone cell, where each arrangement represents a color or colors whichhave been converted to grayscale. However, this approach fails toprovide reliable and sufficient retention of the color information dueto inevitable dot gain that blends or obfuscates the individual pixels.This makes it difficult to determine both the number of pixels beingprinted as well as the particular arrangement which is being representedin the halftone cell. As a result, a wrong color or no color may beassociated with a particular pixel arrangement that has been printed ina monochrome image.

The present invention addresses these and other problems associated withthe prior art.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example block diagram of a monitor and a graphicdevice.

FIG. 2 illustrates an example block diagram of a processor and a colorindex table.

FIG. 3 illustrates an example screen known in the art, includingmultiple halftone cells.

FIG. 4 illustrates a further example screen known in the art.

FIG. 5 illustrates an example screen or device space including ahalftone segment and a white segment.

FIG. 6 illustrates an example color index table.

FIG. 7A illustrates an example operation of an image understandingalgorithm including the example screen of FIG. 5.

FIG. 7B illustrates an example operation of a further embodiment of animage understanding algorithm.

FIG. 7C illustrates an operation of yet another embodiment of an imageunderstanding algorithm.

FIG. 8 illustrates a method of selecting a target color and assigning afactor index.

FIG. 9 illustrates a method of scanning an image and identifying afactor index associated with a color.

SUMMARY OF THE INVENTION

An image processing system is herein disclosed as including a processorconfigured to analyze a color image to determine a set of target colorsand a database including factor profiles associated with a set of storedcolors. The image processing system further includes a printercontroller that assigns the factor profiles to the target colorsaccording to a color space proximity of the target colors with thestored colors. The factor profiles represent a combination of factorsincluding a gray level and a screen angle.

A method is herein disclosed of analyzing a target color in a colorimage, selecting a group of factor profiles associated with a printedimage and prioritizing the factor profiles according to an ease ofidentification. The method further includes converting the target colorto a grayscale and assigning the factor profiles to the target coloraccording to the priority of the factor profiles.

Logic is further herein disclosed that is encoded in one or moretangible media for execution and when executed operable to scan aprinted image, segment the scanned image into white and halftonesegments, and locate a prime pixel in a high density area of thehalftone segment. The logic is further operable to identify a detectionline passing through the prime pixel, determine a screen angleassociated with the detection line, identify a factor index associatedwith the screen angle, and associate the factor index with a color.

The invention will become more readily apparent from the followingdetailed description of a preferred embodiment of the invention whichproceeds with reference to the accompanying drawings.

DESCRIPTION OF EXAMPLE EMBODIMENTS

Whereas color images may be printed as color prints, they may also beconverted to grayscale and printed as monochrome prints. Colorconversion to grayscale may be accomplished when a printer is onlycapable of printing monochrome prints, for example when it only includesa black toner. In other instances, a user may want to print the colorimage as a monochrome image for effect, and selectively convert thecolor to grayscale using a color rendering algorithm. In yet othersituations, a monochrome print may be selected in order to conservecolor toner or to preview a document.

Regardless of the reason for rendering a color print as a monochromeprint, there exist various ways of performing halftone operations anddithering patterns that are intended to render the color print as amonochrome print in an aesthetically pleasing manner. In some instances,more than one color may be represented as the same shade or tone in themonochrome print. This may be a function of the relatively limitednumber of gray levels available to a conventional printer compared withthe large number of colors that may be displayed with a conventionalmonitor. In many cases, it may not matter to a viewer of a monochromeprint if the selected gray level is representative of a light green or alight red for example. Two colors that may normally appear to be quitdistinct to a person in a color image may instead be viewed as theidentical gray level in the monochrome image so as to beindistinguishable from one another.

In some cases, it may not matter if a person is able to distinguish ordetermine what color is being represented by the selected gray level.Furthermore, it may be possible to refer to the original color image todetermine the associated input colors. Where the original color image isnot conveniently accessible, it may nevertheless be of interest todetermine what colors are being represented in the monochrome image.However, it may not be practical to represent all of the displayedcolors using only the limited number of gray levels available to theconventional printer.

Twenty four bits of color information may be used to specify a colordisplayed on a typical monitor that includes eight bits of data per eachof three color channels. In practice, less bits may be used that willstill provide an acceptable color palette for a human observer. Forexample, a nine bit color palette will provide an array of colors thatwill satisfy many user applications. A conventional printer may only beable to print a limited number of unique gray levels. In some cases aprinter may print up to 101 gray levels for any given halftone dot. Byincluding other printing features and characteristics other than graylevel, retention of color information in a monochrome or grayscale imagemay be achieved.

FIG. 1 illustrates an example block diagram of a monitor 5 and a graphicdevice 10. The monitor 5 may include any conventional display deviceused to project an image. The projected image may be a color image, suchas color image 20. The graphic device 10 may include any device capableof printing an image on a printed media. The printed image may beprovided as a monochrome or grayscale image, such as monochrome image30.

The color image 20 may be displayed or projected by the monitor 5 asincluding colors such as background color 22 and image color 25. Thecolors 22, 25 may be converted to grayscale by the graphic device 10, ora computer associated with the monitor 5 and graphic device 10, tocreate monochrome image 30. The monochrome image 30 may include aprinted or scanned image having grayscale colors such as background tone32 and image tone 35. Background tone 32 may be understood asrepresenting a color conversion of background color 22. Similarly, imagetone 35 may be understood as representing a color conversion of imagecolor 25. Monochrome tones 32, 35 may be printed as grayscale or anotherprintable color. In one embodiment, a black toner may be used to printthe monochrome tones 32, 35.

The graphic device 10 may include a print controller or processor 75that converts the color image 20 into the monochrome image 30, includingan image understanding algorithm for recording color information intothe grayscale colors. In one embodiment the graphic device 10 is ascanner that includes processing capabilities for interpreting the colorinformation from the monochrome image 30. Graphic device 10 may includeprinting capabilities, scanning capabilities, or both.

FIG. 2 illustrates an example block diagram of a processor 100 and acolor index table 50. The processor 100 may be provided in a computer,graphic device, printer, scanner or other device including processingcapability. In one embodiment, the processor 100 includes a printcontroller. Processor 100 may convert the color image 20 into themonochrome image 30. The processor 100 may include an imageunderstanding algorithm for recording color information into themonochrome image 30, or for interpreting the color information from themonochrome image 30. In one embodiment, the processor 100 is provided inthe graphic device 10 as processor 75 of FIG. 1. The processor 100 maybe associated with processing functions related to printing, scanning,or both.

FIG. 3 illustrates an example screen 72 known in the art, includingmultiple halftone cells 74, 76, 78. Halftone cells typically include aprinted portion including enabled pixels such as printed pixel 80 and awhite portion including disabled pixels such as white pixel 90. Halftonecells 74, 76, 78 may each be understood as including a halftone dotshaped as a line screen, or line pair. A screen frequency may be used toidentify the number of halftone cells per unit distance.

Screen frequency 45 may be determined by counting the number of halftoneline pairs per inch. For clarity and simplicity of representation, thescreen 72 illustrates an example of providing three halftone line pairsper inch, although a typical screen frequency 45 will include more thana hundred such halftone line pairs per inch. Screen frequency 45, whichmay be indicated by the number of lines of halftone cells per inch(LPI), may affect the number of shades of gray that can be displayed orthe resolution of an image that a printer is able to print. Depending ona resolution capability of the printer, the screen frequency and imageresolution may be inversely related.

FIG. 4 illustrates a further example screen known in the art, includingmultiple halftone cells 42, 44, 46 and 48. Halftone cell 42 is shown asincluding a single printed pixel 80 surrounded by 14 white pixels, suchas white pixel 90. Halftone cell 44 is shown as including two printedpixels. Halftone cell 46 is shown as including four printed pixels.Halftone cell 48 is shown as including nine printed pixels. The level ofgray associated with any of the halftone cells 42, 44, 46, 48 may bedetermined by the number of printed pixels as well as the shape of thehalftone cell. More printed pixels may be associated with a darker levelof gray. Halftone cells which include clustered pixels may appear as adarker gray level than a halftone cell including an equal number ofpixels arranged in a scattered pattern. Halftone cell 44 may beunderstood as having a darker gray level than halftone cell 42, wherehalftone cell 42 has the lightest gray level of the four halftone cells.Halftone cell 46 may be understood as having a darker gray level thanhalftone cell 44. Halftone cell 48 may be understood as having a darkergray level than halftone cell 46, where halftone cell 48 has the darkestgray level of the four halftone cells.

FIG. 5 illustrates an example screen or print space 120 including ahalftone segment 180 and a white segment 190. Halftone segment 180 mayinclude multiple halftone cells and halftone dots. Screen 120illustrated in FIG. 5 is shown as including diamond shaped halftonedots. The white segment 190 is the area of the screen 120 that does notinclude any halftone dots. The white segment 190 may be understood asbeing paper white.

Screen 120 may be understood as being part of a print space including aprinted image, such as monochrome image 30 of FIG. 1. For example,screen 120 may be associated with the image tone 35. The proximity ofprinted pixels, halftone dots and their amount of overlap may be used todetermine a gray level for the screen 120 and hence the image tone 35.

In one embodiment, the screen 120 is part of a scanned image. Forexample a printed image may be scanned by the graphic device 10 ofFIG. 1. The halftone segment 180 may be understood as having pixelswhich are enabled or turned on, whereas the white segment 190 may beunderstood has having the pixels disabled or turned off. A processor,such as processor 100 of FIG. 2 may be used to segment the scanned imageinto the halftone segment 180 and the white segment 190.

One of the printed or enabled pixels may be identified as a prime pixel105 that is located in an approximate center of the screen 120, or in ahigh density area of the halftone segment 180. A detection line 95 isidentified as passing through the prime pixel 105 and intersecting thegreatest number of adjacent or neighboring pixels. A frequency line 85is identified as being formed at an angle 200 to the detection line. Inone embodiment, the angle 200 is provided as forty five degrees.

A halftone segment 110 is identified as being formed about anapproximate center point at or near the prime pixel 105. The halftonesegment is shown as including thirty six pixels arranged in a six by sixpixel arrangement, although it may include fewer or more of the pixelsin the screen 120. In one embodiment, a gray level for the halftonesegment 110 is identified according to a density of printed or enabledpixels in a localized area around the prime pixel 105.

FIG. 6 illustrates an example of a color index table such as the colorindex table 50 of FIG. 2. Color index table 50 may be included in atable or database, which is accessible to a processor, such as processor100 of FIG. 2. The color index table 50 may include a factor profile 66and multiple fields associated with one or more entries. One of thefields may include a gray level 55 of the scanned or printed monochromeimage. The gray level 55 may be provided a value L that identifies apercentage or number of bits that have been printed or enabled in ahalftone cell or halftone segment, such as halftone segment 110 of FIG.5. In one embodiment, the gray level 55 is normalized by normalizingvalue of (255), where (255) is associated with 100% black and (0) isassociated with 0% black, or paper white.

Another field in the color index table 50 may be provided to identify afactor index 60. The factor index 60 may include factors such ashalftone dot shape S, screen angle A and screen frequency F. The factordot shape S may identify any of a line screen, Euclidian screen, diamonddot, round dot, elliptical dot, square dot or any other dot shape knownin the art. In one embodiment, the factor dot shape S includes clustertype dot shapes, where the enabled or printed pixels are centralized orclustered about each other. Dot shapes that include dispersed orscattered pixels may also be described by the factor dot shape S whichidentifies the pixel pattern or arrangement. A dot size may also beconsidered in addition to, or as part of, the dot shape S. For example,a large square halftone dot may be associated with a different dot shapeS than a small halftone square dot.

The factor screen angle A may identify the screen angle 200 illustratedin FIG. 5. The screen angle A may include values such as 0, 15, 30, 45,60, 75, 90, 105, 120, 135, and 165 degrees. In one embodiment twelvedifferent screen angles A may be identified in the color index table 50.More or fewer screen angles A may be printed or detected. The factorscreen frequency F may identify the screen frequency 45 of FIG. 4.Screen frequency F may include a number of rows or lines of halftonecells per inch LPI. In one embodiment, each of the factors S,A,F areprovided as separate fields in the color index table 50.

Another field in the color index table 50 may be provided to identify afactor priority 65 associated with the factor index 60. The factorpriority 65 may be assigned according to a confidence level orprocessing speed of detecting one or more of the factors S,A,F in aprinted or scanned image, such as monochrome image 30 of FIG. 1. In oneembodiment, the factor priority 65 is provided as a scaled, numericvalue N associated with the ease of detecting one or more of the factorsS,A,F.

In addition, a field may be provided in the color index table 50 thatidentifies a target color 70. Target color 70 may be associated with thefactor index 60 and the gray level 55. More than one target color 70 maybe associated with the same gray level 55. For example, two targetcolors may be associated with a gray level L, whereas a first targetcolor is further associated with a first index factor and the secondtarget color is associated with a second index factor. The first andsecond target colors may be included as different entries in the colorindex table 50. The target color 70 may be defined in a red, green, blueRGB color space, in which case the target color may be identified by aRGB color tuple. The factor profile 66 may include any or all of thegray level 55, the factor index 60, the factor priority 65 and thetarget color 70.

The processor 100 of FIG. 2 may be used to detect or identify one ormore target colors such as colors 22, 25 associated with color image 20in FIG. 1. The target color 25 may be compared to the list of storedtarget colors 70 in the color index table 50 in order to determine abest color match between the target color 25 and the stored color 70. Inone embodiment, color vector error diffusion may be used to measure thetarget color 25 and analyze it to determine a stored color 70 that hasthe shortest color distance from the target color 25. A print controlleror processor, such as processor 100 of FIG. 2 may assign a factorprofile or factor index 60 according to the color space proximitybetween the target color 25 and the stored color 70. Any or all of thevalues for gray level L, dot shape S, screen angle A and screenfrequency F may be used to associate the factor profile 66 with thetarget color 25.

The gray level 55 and factor index 60 may be used to retrieve colorinformation from an image, such as monochrome image 30, or to record orencode color information into the monochrome image 30. The gray level Land factors S,A,F may be incorporated or encoded into a grayscale ormonochrome image 30 to retain a memory of the target colors associatedwith a color image, such as color image 20 of FIG. 1.

Each of the factors S,A,F or the factor index 60 may be assigned apriority according to an ease of detection in grayscale or monochromeimage. The ease of identification may be determined according to aconfidence level or processing speed of detecting the factors S,A,F inthe grayscale image.

In one embodiment, there are twelve screen angles associated with screenangle A, four dot shapes associated with dot shape S and fourfrequencies associated with screen frequency F. Each combination ofscreen angle A, dot shape S and screen frequency F may be associatedwith a different gray level L. Each combination may be identified by afactor index 60 or a factor profile 66. If we assume there are 101different gray levels, and for each gray level there are 12×4×4 or 96factor indices, this may result in accommodating approximately fourteenbits of color information in the monochrome image. Some applications usean index color space may include a subset of the available monitorcolors. Nine or ten bits of color information may be sufficient torepresent the index color space.

Gray levels that are near 0% or near 100% may have fewer combinations offactors available to them due to the size of the halftone dot associatedwith each. Gray levels of 0% and 100% may only have one factor index 60associated with them. Increasing the number or type of screen angle A,dot shape S or screen frequencies F may serve to accommodate additionalbits of color information up to and including the total number of colorbits that may be displayed by a monitor.

FIG. 7A illustrates an example operation of an image understanding IUalgorithm for analyzing an image, such as monochrome image 30 of FIG. 1,including the example print space or screen 120 of FIG. 5. The IUalgorithm may be performed by a processor such as processor 100 of FIG.2. The detection line 95 may be used to determine the screen angle A ofthe screen 120. The frequency line 85 may be used to determine thescreen frequency F of the screen 120. Similarly, a diamond dot halftoneshape 125 and associated gray levels may be analyzed by the processor100 to determine the target color 70 associated with the factor profile66 in the color index table 50. In this example operation, the screen120 is determined by the processor 100 to be associated with a squareimage including target color 130. Both the target color 130 and theshape or arrangement of pixels may therefore be encoded and retained inthe screen 120.

FIG. 7B illustrates an example operation of a further embodiment of animage understanding algorithm when operated on a further example printspace or screen 140. Screen 140 may be analyzed by the processor 100 todetermine detection line 144 and frequency line 142. The square dothalftone shape 145 and associated gray levels may be analyzed by theprocessor 100 to determine the target color 70 associated with thefactor profile 66 in the color index table 50. In this exampleoperation, the screen 130 is determined by the processor 100 to beassociated with a circular image including target color 150. Both thetarget color 150 and the shape or arrangement of pixels may therefore beencoded and retained in the screen 130.

FIG. 7C illustrates an operation of yet another embodiment of an imageunderstanding algorithm including a print space or screen 160. Screen160 may be analyzed by the processor 100 to determine detection line 164and frequency line 162. The line screen dot halftone shape 165 andassociated gray levels may be analyzed by the processor 100 to determinethe target color 70 associated with the factor profile 66 in the colorindex table 50. In this example operation, the screen 160 is determinedby the processor 100 to be associated with a triangular image includingtarget color 170. Both the target color 170 and the shape or arrangementof pixels may therefore be encoded and retained in the screen 140.

FIG. 8 illustrates a method of selecting a target color, such as targetcolor 70 of FIG. 6, and assigning the factor index 60 identifying thefactor profile 66. At operation 810, a target color in a color imagesuch as color image 20, is selected and analyzed. The target color maybe statistically analyzed to determine a frequency of use

At operation 820, a group of factors associated with a printed image areselected. The factor may include factors such as a gray level L, ahalftone dot shape S, a screen angle A, and a screen frequency F. Thefactor profile 66 may be associated with the factors S,A,F and thefactor index 60.

At operation 830, the factor profiles 66 are prioritized according to anease of identification of the factors. The ease of identification may bemade with respect to one of the factors or a combination of factors. Theease of identification may be determined according to a processing speedof detecting the factor profiles 66 in a scanned grayscale image. In oneembodiment, a line screen dot shape is the easiest to detect. In anotherembodiment, screen angles of 0, 45, 90 and 135 degrees are easiest todetect. In yet another embodiment, lower screen frequencies are easierto detect.

At operation 840, the target color is converted to a gray level using aselected algorithm. Each of the color pair values between the targetvalue and the converted gray level may be recorded. One or more targetvalues may be converted to the same gray level.

At operation 850, the factor profiles 66 are assigned to the targetcolor according to the priority of the factor profiles 66. Where morethan one target value has been converted to the gray level, the mostfrequent target color may be associated with the factor profile 66 thathas been identified as being the highest priority, or the easiest toidentify.

FIG. 9 illustrates a method of scanning an image and identifying afactor index 60 associated with color. At operation 910, a printed imageis scanned, for example as monochrome image 30 of FIG. 1.

At operation 920, the scanned image is segmented into differentsegments, for example the white segment 190 and the halftone segment 180illustrated in FIG. 5.

At operation 930, a prime pixel 105 is located. The prime pixel 105 maybe located at or near the center of a high density area of the halftonesegment 180.

At operation 940, a detection line 95 is identified. The detection line95 may be identified as passing through the prime pixel 105. In oneembodiment, the detection line 95 is determined according to anintersection of the detection line 95 with the greatest number ofpixels.

At operation 950, a screen angle A associated with the detection line 95is determined. In one embodiment, the screen angle A is measuredclockwise in degrees, where zero degrees is determined at 9:00 on a 12hour clock. A screen frequency F of the halftone segment 180 may also bedetected. In one embodiment, the screen frequency F is detected along afrequency line 85 inclined forty five degrees from the detection line95.

At operation 960, a factor index 60 associated with the screen angle Ais identified. The factor index 60 may further be associated with thescreen frequency F, the dot shape S, and the gray level L. The graylevel L for the halftone segment 180 may be determined according to apixel density in a localized area around the prime pixel 105.

At operation 970, the factor index 60 is associated with a color, forexample the target color 70 identified in the color index table 50 ofFIG. 6. The color information may therefore be reclaimed from themonochrome image 30, where the monochrome image 30 was previouslyrendered from a color image, such as color image 20. The colorinformation may be use to restore the color image 20 using stored targetcolors that approximate the original colors rendered from the colorimage 20. In one embodiment, the factor indices 60 are associated withthe stored target colors 70.

The system described above can use dedicated processor systems, microcontrollers, programmable logic devices, or microprocessors that performsome or all of the operations. Some of the operations described abovemay be implemented in software and other operations may be implementedin hardware.

For the sake of convenience, the operations are described as variousinterconnected functional blocks or distinct software modules. This isnot necessary, however, and there may be cases where these functionalblocks or modules are equivalently aggregated into a single logicdevice, program or operation with unclear boundaries. In any event, thefunctional blocks and software modules or features of the flexibleinterface can be implemented by themselves, or in combination with otheroperations in either hardware or software.

Having described and illustrated the principles of the invention in apreferred embodiment thereof, it should be apparent that the inventionmay be modified in arrangement and detail without departing from suchprinciples. We claim all modifications and variation coming within thespirit and scope of the following claims.

1. An image processing system comprising: a database including factorprofiles associated with stored monochrome colors; a printer controllerthat assigns the factor profiles to target colors determined from acolor image according to a color space proximity of the target colorswith the stored monochrome colors, where the factor profiles represent acombination of factors including a gray level and a screen angle, whereeach of the factor profiles identifies a monochrome color having adifferent combination of the gray level and the screen angle, and wherethe gray level and the screen angle are incorporated into a monochromeimage comprising the stored monochrome colors to retain a memory of thetarget colors associated with the color image; and a processorconfigured to: analyze the color image to determine the target colors;locate a prime pixel in a high density area of the monochrome image; andassociate the screen angle of the monochrome image as passing throughthe prime pixel and through a highest number of pixels in a vicinity ofthe prime pixel.
 2. The image processing system according to claim 1where each of the factors are assigned a priority according to an easeof detection in the monochrome image.
 3. The image processing systemaccording to claim 2 where the ease of detection is determined accordingto a confidence level of detecting the factors in the monochrome image.4. The image processing system according to claim 1 where the factorsfurther include a screen frequency.
 5. The image processing systemaccording to claim 4 where the screen angle and the screen frequency aredetermined by selecting a detection line passing through the highestnumber of pixels.
 6. The image processing system according to claim 1where the factors further include a cluster type dot shape.
 7. The imageprocessing system according to claim 1 where a first screen anglepassing through the prime pixel is associated with a first target color,where a second screen angle passing through the prime pixel isassociated with a second target color, and where both the first andsecond target colors are associated with a same gray level.
 8. A methodcomprising: analyzing a target color in a color image; locating a primepixel in a high density area associated with a monochromaticrepresentation of the color image; associating a screen angle of themonochromatic representation as passing through the prime pixel andthrough a highest number of pixels in a vicinity of the prime pixel;selecting a group of factor profiles associated with the monochromaticrepresentation, where the factor profiles comprise one or more factorsincluding the screen angle; prioritizing the factor profiles accordingto an ease of identification of the one or more factors in themonochromatic representation; converting the target color to amonochrome color; assigning a factor profile to the target color based,at least in part, on the priority of the factor profiles; and printingthe monochromatic representation with a printer, where the monochromaticrepresentation comprises the monochrome color and the one or morefactors, and where a memory of the target color is retained in themonochromatic representation as a combination of the monochrome colorand the assigned factor profile.
 9. The method according to claim 8where the one or more factors further include a screen frequency. 10.The method according to claim 8 where the one or more factors furtherinclude a dot shape.
 11. The method according to claim 8 where the easeof identification is determined according to a processing speed ofdetecting the factor profiles in a scanned monochrome image.
 12. Themethod according to claim 8, further comprising: scanning the printedmonochromatic representation; identifying the monochrome color and theone or more factors from the scanned monochromatic representation;associating the monochrome color and the one or more factors with thetarget color; and restoring the color image comprising the target color.13. The method according to claim 12, further comprising: identifying adetection line passing through the prime pixel; and determining thescreen angle corresponding with the detection line.
 14. A non-transitorycomputer readable medium having stored thereon computer-executableinstructions that, in response to execution by a computing device of asystem, cause the system to: scan a printed image; segment the scannedimage into white and halftone; locate a prime pixel in a high densityarea of the halftone segment; identify a detection line passing throughthe prime pixel and through a highest number of pixels in the highdensity area; determine a screen angle associated with the detectionline; identify a factor index associated with the screen angle;associate the factor index with a color; reclaim the color from theprinted image, where the printed image is a monochrome image that wasrendered from a color image; and restore the color image using storedcolors that approximate original colors rendered from the color image,where the factor index is associated with one of the stored colors. 15.The non-transitory computer readable medium according to claim 14 whereexecution of the computer-executable instructions by the computingdevice further causes the system to detect a screen frequency of thehalftone segment along a frequency line inclined forty five degrees fromthe detection line.
 16. The non-transitory computer readable mediumaccording to claim 14 where execution of the computer-executableinstructions by the computing device further causes the system todetermine the screen angle of the detection line according to anintersection with the highest number of pixels.
 17. The non-transitorycomputer readable medium according to claim 14 where execution of thecomputer-executable instructions by the computing device further causesthe system to determine a gray level for the halftone segment accordingto a pixel density in a localized area around the prime pixel.
 18. Thenon-transitory computer readable medium according to claim 17 where thefactor index is further associated with the gray level.
 19. Thenon-transitory computer readable medium according to claim 14 where themonochrome image consists of black toner printed on paper, and where thecolor image is displayed on a monitor including the stored colors of RedGreen Blue (RGB) color tuples.
 20. A method comprising: scanning aprinted image; segmenting the scanned image into white and halftone;locating a prime pixel in a high density area of the halftone segment;identifying a detection line passing through the prime pixel and througha highest number of pixels in the high density area; determining ascreen angle associated with the detection line; identifying a factorindex associated with the screen angle; associating the factor indexwith a color; reclaiming the color from the printed image, where theprinted image is a monochrome image that was rendered from a colorimage; and restoring the color image using stored colors thatapproximate original colors rendered from the color image, where thefactor index is associated with one of the stored colors.